Location
Havener Center, Miner Lounge / Wiese Atrium, 9:30am-11:30am
Start Date
4-2-2026 9:30 AM
End Date
4-2-2026 11:30 AM
Presentation Date
April 2, 2026; 9:30am-11:30am
Description
Accurate hydrologic prediction at relevant spatial scales is essential for flood risk management. This study explores how spatial scale affects model parameters and simulation outcomes in the Hillslope Link Model (HLM). This was motivated by HLM implementation within the Next Generation Water Resources Modeling (NextGen) framework for the U.S. National Water Model. Since NextGen alters HLM's spatial scale from hillslopes to catchments, we assess how this change affects runoff generation and routing. We implement HLM at both scales using identical, predetermined parameters without calibration to isolate spatial discretization effects. Using approximately ten years of precipitation and streamflow data from watersheds in Iowa and Missouri, we evaluate model performance across varying basin sizes. Our analysis identifies key parameters that contribute to differences in model behavior between scales. These findings improve understanding of parameter sensitivity and support more effective calibration strategies for scale-dependent hydrologic modeling.
Biography
Hari Dhital completed his undergraduate degree in civil engineering from Tribhuvan University, Nepal, and is currently enrolled in a PhD program in civil engineering at the Missouri University of Science and Technology under the supervision of Dr. Bong-Chul Seo. His research interests include hydrologic modeling, rainfall forecasting using machine learning approaches, and climate change. His work focuses on improving streamflow prediction, evaluating spatial scale effects in hydrologic systems, and integrating geospatial datasets with advanced modeling frameworks to better understand watershed behavior and support sustainable water resource management.
Meeting Name
2026 - Miners Solving for Tomorrow Research Conference
Department(s)
Civil, Architectural and Environmental Engineering
Document Type
Poster
Document Version
Final Version
File Type
event
Language(s)
English
Rights
© 2026 The Authors, All rights reserved
Included in
Assessing the Effects of Scale-Dependent Representation of River Networks on Hydrologic Prediction
Havener Center, Miner Lounge / Wiese Atrium, 9:30am-11:30am
Accurate hydrologic prediction at relevant spatial scales is essential for flood risk management. This study explores how spatial scale affects model parameters and simulation outcomes in the Hillslope Link Model (HLM). This was motivated by HLM implementation within the Next Generation Water Resources Modeling (NextGen) framework for the U.S. National Water Model. Since NextGen alters HLM's spatial scale from hillslopes to catchments, we assess how this change affects runoff generation and routing. We implement HLM at both scales using identical, predetermined parameters without calibration to isolate spatial discretization effects. Using approximately ten years of precipitation and streamflow data from watersheds in Iowa and Missouri, we evaluate model performance across varying basin sizes. Our analysis identifies key parameters that contribute to differences in model behavior between scales. These findings improve understanding of parameter sensitivity and support more effective calibration strategies for scale-dependent hydrologic modeling.
Comments
Advisor: BongChul Seo, bongchul.seo@mst.edu